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Improved detection algorithm and made structural changes.

master
Stelios Giakoumidis 5 years ago
parent
commit
6cc191b629
  1. 73
      camera module/main.py

73
camera module/main.py

@ -4,16 +4,19 @@ import cv2
DESIRED_HEIGHT = 480 # The input image will be resized to this height, preserving its aspect ratio. DESIRED_HEIGHT = 480 # The input image will be resized to this height, preserving its aspect ratio.
BLUE_THRESHOLD = 150 # If the blue channel is bigger than this, it is considered background and removed. BLUE_THRESHOLD = 150 # If the blue channel is bigger than this, it is considered background and removed.
BINARY_THRESHOLD = 1 # If the pixel is not brighter than this, it is removed before detection. BINARY_THRESHOLD = 1 # If the pixel is not brighter than this, it is removed before detection.
LINE_THICKNESS = 2 # Thickness of the drawn lines.
BLUR_KERNEL_SIZE = 3 # The size of the Gaussian blur kernel.
DILATION_KERNEL_SIZE = 5 # The size of the dilation kernel.
DILATION_ITERATIONS = 5 # The number of dilation iterations.
# Colors (assuming the default BGR order).
# Colors (assuming BGR order).
RED = (0, 0, 255) RED = (0, 0, 255)
GREEN = (0, 255, 0) GREEN = (0, 255, 0)
BLUE = (255, 0, 0) BLUE = (255, 0, 0)
YELLOW = (0, 255, 255) YELLOW = (0, 255, 255)
# Function definitions # -------------- Function definitions -----------------------------
def resizeImage(img): def resizeImage(img):
"Resize the input image based on the DESIRED_HEIGHT variable." "Resize the input image based on the DESIRED_HEIGHT variable."
p = img.shape; p = img.shape;
@ -22,31 +25,34 @@ def resizeImage(img):
img = cv2.resize(img, ( DESIRED_HEIGHT, int(width) )) img = cv2.resize(img, ( DESIRED_HEIGHT, int(width) ))
return img return img
##################################################################################### def processImage(img):
# Read image from source
img = cv2.imread('/home/stelios/Desktop/IoT/Talos_Drones_Tracking_and_Telemetry/camera module/drone.jpg', cv2.IMREAD_COLOR)
# Resize image to the desired height. # Resize image to the desired height.
img = resizeImage(img) resized = resizeImage(img)
imgOriginal = img.copy() dim = resized.shape
# Remove BLUE # Remove BLUE
p = img.shape noBlue = resized.copy()
for i in range(p[0]): for i in range(dim[0]):
for j in range(p[1]): for j in range(dim[1]):
if (img[i,j,0] > BLUE_THRESHOLD): if (resized[i,j,0] > BLUE_THRESHOLD):
img[i,j,:] = 0 noBlue[i,j,:] = 0
# Convert to grayscale. # Convert to grayscale.
img = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY) gray = cv2.cvtColor(noBlue, cv2.COLOR_BGR2GRAY)
# Blur the image.
blur = cv2.GaussianBlur(gray, (BLUR_KERNEL_SIZE, BLUR_KERNEL_SIZE), 0)
# Threshold the image and find its contours. # Threshold the image and find its contours.
thres, imgThres = cv2.threshold(img, BINARY_THRESHOLD, 255, cv2.THRESH_BINARY) _, imgThres = cv2.threshold(blur, BINARY_THRESHOLD, 255, cv2.THRESH_BINARY)
img2, contours, hierarchy = cv2.findContours(imgThres, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
# Find the biggest contour. # Dilate the image.
dilated = cv2.dilate(imgThres, (DILATION_KERNEL_SIZE,DILATION_KERNEL_SIZE), iterations=DILATION_ITERATIONS)
# Find the largest image contour.
_, contours, hierarchy = cv2.findContours(dilated, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
maxContour = max(contours, key = cv2.contourArea) maxContour = max(contours, key = cv2.contourArea)
''' '''
@ -59,12 +65,31 @@ cv2.drawContours(imgOriginal, hull, -1, (255,0,0), 3)
x,y,w,h = cv2.boundingRect(maxContour) x,y,w,h = cv2.boundingRect(maxContour)
# Get the centroid of the rectangle. # Get the centroid of the rectangle.
centerX = int( (x + x + w) / 2) objCenterX = int( (x + x + w) / 2)
centerY = int( (y + y + h) / 2) objCenterY = int( (y + y + h) / 2)
imgCenterX = int(dim[1]/2)
imgCenterY = int(dim[0]/2)
# Draw the bounding rectangle and its centroid to the image. # Draw the bounding rectangle and its centroid to the image.
cv2.circle(imgOriginal, (centerX, centerY), 5, YELLOW, 2) cv2.circle(resized, (objCenterX, objCenterY), 5, YELLOW, LINE_THICKNESS)
cv2.rectangle(imgOriginal, (x,y), (x+w,y+h), RED, 2) cv2.rectangle(resized, (x,y), (x+w,y+h), RED, LINE_THICKNESS)
return resized
#####################################################################################
# Read image from source
img = cv2.imread('/home/stelios/Desktop/IoT/Talos_Drones_Tracking_and_Telemetry/camera module/drone.jpg', cv2.IMREAD_COLOR)
# Process the image and get the output.
output = processImage(img)
cv2.imshow('Output', output)
cv2.imshow('Output', imgOriginal) # Terminate if the escape key is pressed or the window is closed.
cv2.waitKey(0) while True:
k = cv2.waitKey()
if k == 27 or k == 255:
break
cv2.destroyAllWindows()
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